Related papers: DRL-Based Antenna Position Optimization For MA-Ass…
Orthogonal time frequency space (OTFS) modulation has demonstrated significant advantages in high-mobility scenarios in future 6G networks. However, existing channel estimation methods often overlook the structured sparsity and clustering…
Delay-Doppler alignment modulation (DDAM) is a novel technique to mitigate time-frequency doubly selective channels by leveraging the high spatial resolution offered by large antenna arrays and multi-path sparsity of millimeter wave…
Six-dimensional movable antenna (6DMA) has been identified as a new disruptive technology for future wireless systems to support a large number of users with only a few antennas. However, the intricate relationships between the signal…
This paper presents a novel deep reinforcement learning (DRL)-based control strategy for achieving precise and robust output voltage regulation in LCC-S resonant converters, specifically designed for wireless power transfer applications.…
This paper investigates a movable antenna (MA) enabled integrated sensing and communication (ISAC) system under the influence of antenna crosstalk. First, it generalizes the antenna crosstalk model from the conventional fixed-position…
The six-dimensional movable antenna (6DMA) is a promising technology to fully exploit spatial variation in wireless channels by allowing flexible adjustment of three-dimensional (3D) positions and rotations of antennas at the transceiver.…
In this paper, we present a new wireless sensing system utilizing a movable antenna (MA) that continuously moves and receives sensing signals to enhance sensing performance over the conventional fixed-position antenna (FPA) sensing. We show…
Deep learning models for channel estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems often suffer from performance degradation under fast-fading channels and low-SNR scenarios. To address these limitations, we introduce…
The escalating interests on underwater exploration/reconnaissance applications have motivated high-rate data transmission from underwater to airborne relaying platforms, especially under high-sea scenarios. Thanks to its broad bandwidth and…
This paper presents a novel heuristic deep reinforcement learning (HDRL) framework designed to optimize reconfigurable intelligent surface (RIS) phase shifts in secure satellite communication systems utilizing rate splitting multiple access…
The rapid proliferation of unmanned aerial vehicle (UAV) applications imposes stringent requirements on continuous and reliable communication coverage in low-altitude airspace. Conventional cellular systems built upon fixed-position…
This paper proposes a two-scale spatial deployment strategy to ensure reliable coverage for multiple target areas, integrating macroscopic intelligent reflecting surfaces (IRSs) and fine-grained movable antennas (MAs). Specifically, IRSs…
The advent of fifth generation (5G) networks has opened new avenues for enhancing connectivity, particularly in challenging environments like remote areas or disaster-struck regions. Unmanned aerial vehicles (UAVs) have been identified as a…
Non-terrestrial base stations (NTBSs), including high-altitude platform stations (HAPSs) and hot-air balloons (HABs), are integral to next-generation wireless networks, offering coverage in remote areas and enhancing capacity in dense…
Movable antenna (MA) technology is highly promising for improving communication performance, due to its advantage of flexibly adjusting positions of antennas to reconfigure channel conditions. In this paper, we investigate MAs-assisted…
Orthogonal Time Frequency Space ({OTFS}) modulation offers significant advantages over Orthogonal Frequency Division Multiplexing ({OFDM}), particularly in high speed environments. Hence, we consider {OTFS} transmission over high-Doppler…
In this correspondence, we study deploying movable antenna (MA) array in a wideband multiple-input-single-output (MISO) communication system, where near-field (NF) channel model is considered. To alleviate beam squint effect, we propose to…
This paper investigates a novel communication paradigm employing movable antennas (MAs) within a multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) downlink framework, where users are equipped with MAs. Initially,…
In this work, we propose a deep learning (DL)-based approach that integrates a state-of-the-art algorithm with a time-frequency (TF) learning framework to minimize overall latency. Meeting the stringent latency requirements of 6G orthogonal…
Movable antennas (MA) are a novel technology that allows for the flexible adjustment of antenna positions within a specified region, thereby enhancing the performance of wireless communication systems. In this paper, we explore the use of…